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5 ways AI can help mitigate the global shipping crisis

TechCrunch

If you don’t have the data about what is on a ship transporting your materials, then use this crisis as an opportunity to justify prioritizing supply chain digital transformation with data, IoT and advanced analytics (e.g., machine learning and simulation).

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Making Sense of IoT Platforms: AWS vs Azure vs Google vs IBM vs Cisco

Altexsoft

For the most part, they belong to the Internet of Things (IoT), or gadgets capable of communicating and sharing data without human interaction. The number of active IoT connections is expected to double by 2025, jumping from the current 9.9 The number of active IoT connections is expected to double by 2025, jumping from the current 9.9

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Climate tech opportunities for IT pros

CIO

While crucial, if organizations are only monitoring environmental metrics, they are missing critical pieces of a comprehensive environmental, social, and governance (ESG) program and are unable to fully understand their impacts. of survey respondents) and circular economy implementations (40.2%).

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Low-Code Development: Create Applications Without Programming Knowledge

Apiumhub

These platforms are designed to simplify and democratize the development process, enabling individuals with little to no programming experience to create functional applications. This enables data-driven decision-making and improves business intelligence capabilities.

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Hospitality Business Intelligence: Technology Specifics, Integration Problems, Business Value, and Key Providers

Altexsoft

As business grows, these become impossible to analyze and keep track of manually or using spreadsheets. Business intelligence (BI) exists to address the problem of capturing and understanding data. Business intelligence in hotels: sources of data and components. Business intelligence use cases for hotels.

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Machine Learning and Deep Learning: How Does Machine Learning Work?

G2 Crowd Software

Essentially, developers create an algorithm and give the program a large set of data, and the program teaches itself using the data it was given without the intervention of the developer. Once the program performs well enough on its own, the learning stops. Supervised learning. Unsupervised learning. Semi-supervised learning.

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The AI continuum

CIO

Classical machine learning: Patterns, predictions, and decisions Classical machine learning is the proven backbone of pattern recognition, business intelligence, and rules-based decision-making; it produces explainable results. Downsides: Not generative; model behavior can be a black box; results can be challenging to explain.